Modelling in economic evaluation: an unavoidable fact of life

A structured process for the validation of a decision-analytic model: application to a cost-effectiveness model for risk-stratified national breast screening

BACKGROUND

Decision-makers require knowledge of the strengths and weaknesses of decision-analytic models used to evaluate healthcare interventions to be able to confidently use the results of such models to inform policy. A number of aspects of model validity have previously been described, but no systematic approach to assessing the validity of a model has been proposed. This study aimed to consolidate the different aspects of model validity into a step-by-step approach to assessing the strengths and weaknesses of a decision-analytic model.

METHODS

A pre-defined set of steps were used to conduct the validation process of an exemplar early decision-analytic-model-based cost-effectiveness analysis of a risk-stratified national breast cancer screening programme [UK healthcare perspective; lifetime horizon; costs (£; 2021)]. Internal validation was assessed in terms of descriptive validity, technical validity and face validity. External validation was assessed in terms of operational validation, convergent validity (or corroboration) and predictive validity.

RESULTS

The results outline the findings of each step of internal and external validation of the early decision-analytic-model and present the validated model (called 'MANC-RISK-SCREEN'). The positive aspects in terms of meeting internal validation requirements are shown together with the remaining limitations of MANC-RISK-SCREEN.

CONCLUSION

Following a transparent and structured validation process, MANC-RISK-SCREEN has been shown to have satisfactory internal and external validity for use in informing resource allocation decision-making. We suggest that MANC-RISK-SCREEN can be used to assess the cost-effectiveness of exemplars of risk-stratified national breast cancer screening programmes (NBSP) from the UK perspective.

IMPLICATIONS

A step-by-step process for conducting the validation of a decision-analytic model was developed for future use by health economists. Using this approach may help researchers to fully demonstrate the strengths and limitations of their model to decision-makers.

Explorative cost-effectiveness analysis of colorectal cancer recurrence detection with next-generation sequencing liquid biopsy in Spain, France, and Germany

Background

Next-generation sequencing liquid biopsy (NGS-LB) for colorectal cancer (CRC) detection and surveillance remains an expensive technology as economies of scale have not yet been realized. Nevertheless, the cost of sequencing has decreased while sensitivity has increased, raising the question of whether cost-effectiveness (CE) has already been achieved from the perspective of European healthcare systems.

Objectives

This health economic (HE) modeling study explores the CE of NGS-LB for CRC based on direct treatment costs compared to standard care without liquid biopsy in Spain, France, and Germany.

Methods

A structured literature search was used to collect evidence from 2009 to 2020 on the stage-dependent quality of life (quality-adjusted life-years, QALY), efficacy, and total direct treatment costs (TDC) of NGS-LB. A decision-analytic Markov model was developed. Over the remaining lifetime, cumulative life expectancy (LE), TDC, and QALYs were calculated for 60-year-old men and women in CRC stage III with different assumed effects of NGS-LB of 1% or 3% on improved survival and reduced stage progression, respectively.

Results

The use of NGS-LB increases LE by 0.19 years in Spanish men (France: 0.19 years, Germany: 0.13 years) and by 0.21 years in Spanish women (France: 0.21 years, Germany: 0.14 years), respectively. The 3% discounted cost per QALY gained was 35,571.95 € for Spanish men (France: 31,705.15 €, Germany: 37,537.68 €) and 35,435.71 € for Spanish women (France: 31,295.57 €, Germany: 38,137.08 €) in the scenario with 3% improved survival and reduced disease progression. Compared to the other two countries, Germany has by far the highest TDC, which can amount to >80k euros in the last treatment year.

Conclusion

In this explorative HE modeling study, NGS-LB achieves generally accepted CE levels in CRC treatment from the health system perspective in three major European economies under assumptions of small improvements in cancer recurrence and survival. Confirmation of these findings through clinical trials is encouraged.

A new innovative method to measure the cost of war: future with fewer conflicts via harm reduction approaches

BACKGROUND

The destruction of World War I (WWI) and World War II (WWII) changed the world forever. In this analysis, the economic costs of WWI and WWII are considered via a harm reduction approach to highlight the cost of war via the mortality of military personnel. The harm reduction philosophy and homeostasis of a biological cell are utilized as a pragmatic approach and analogy to give a greater context to the findings, despite the omission of civilian casualties and military disabilities.

METHODS

Tangible (e.g., loss of wages, productivity, and contributions) and intangible (e.g., quality of life) costs are estimated based on the value of each military personnel derived from secondary data and a mathematical model. This is the first study to estimate the cost of war based on soldier's mortality during the first and second World War.

RESULTS

Based on the tangible value, the WWI and WWII cost for the military personnel was US$43.204 billion ($13 billion ≤ α ≤ $97 billion) and US$540.112 billion ($44 billion ≤ α ≤ $1 trillion). When the intangible cost is considered, it is estimated that the WWI cost was beyond US$124 trillion ($43 trillion ≤ β ≤ $160 trillion), and the WWII cost was above US$328 trillion ($115 trillion ≤ β ≤ $424 trillion). The sensitivity analyses conducted for WWI and WWII demonstrate different ranges based on tangible and intangible values.

CONCLUSIONS

In the current climate of increasing hostilities, inequalities, global warming, and an ever-changing world, economic prosperities are directly linked to peace, stability, and security. Therefore, any future decisions for military conflicts need to increasingly consider harm reduction approaches by considering the cost of life and potential disabilities for each nations' soldiers, sailors, and pilots.

Research trends in contemporary health economics: a scientometric analysis on collective content of specialty journals

INTRODUCTION

Health economics is a thriving sub-discipline of economics. Applied health economics research is considered essential in the health care sector and is used extensively by public policy makers. For scholars, it is important to understand the history and status of health economics-when it emerged, the rate of research output, trending topics, and its temporal evolution-to ensure clarity and direction when formulating research questions.

METHODS

Nearly 13,000 articles were analysed, which were found in the collective publications of the ten most specialised health economic journals. We explored this literature using patterns of term co-occurrence and document co-citation.

RESULTS

The research output in this field is growing exponentially. Five main research divisions were identified: (i) macroeconomic evaluation, (ii) microeconomic evaluation, (iii) measurement and valuation of outcomes, (iv) monitoring mechanisms (evaluation), and (v) guidance and appraisal. Document co-citation analysis revealed eighteen major research streams and identified variation in the magnitude of activities in each of the streams. A recent emergence of research activities in health economics was seen in the Medicaid Expansion stream. Established research streams that continue to show high levels of activity include Child Health, Health-related Quality of Life (HRQoL) and Cost-effectiveness. Conversely, Patient Preference, Health Care Expenditure and Economic Evaluation are now past their peak of activity in specialised health economic journals. Analysis also identified several streams that emerged in the past but are no longer active.

CONCLUSIONS

Health economics is a growing field, yet there is minimal evidence of creation of new research trends. Over the past 10 years, the average rate of annual increase in internationally collaborated publications is almost double that of domestic collaborations (8.4% vs 4.9%), but most of the top scholarly collaborations remain between six countries only.

A review of cost-effectiveness analysis: From theory to clinical practice

Cost-effectiveness analysis has long been practiced; registries date back to the United States of America War Department in 1886. In addition, everyone does intuitive cost-effectiveness analyses in their daily lives. In routine medical care, health economic assessment becomes increasingly important due to progressively limited resources, rising demands, population increases, and continuous therapeutic innovations. The health economic assessment must analyze the outcomes and costs of actions and technologies as objectively as possible to guarantee efficient assessment of novel interventions for Public Health Policy. In other words, it is necessary to determine how much society or patients are willing to or able to pay for novel interventions compared with existing alternatives, given the available resources. In addition, increased cost may displace other health care services already provided in case of fixed budget health care systems. To conduct such analyses, researchers must use standard methodologies and interpretations in light of regional characteristics according to social and economic determinants as well as clinical practice. Such an approach may be essential for transforming the current healthcare system to a value-based model. In this narrative review, concepts of the importance of and some approaches to health economic evaluation in clinical practice will be discussed.

Economic evaluation of fluoride varnish application in preschoolers: A systematic review

BACKGROUND

Fluoride varnish (FV) is a convenient way of professionally applying fluoride in preschoolers. However, its modest anticaries effect highlights the need for economic evaluations.

AIM

To assess economic evaluations reporting applications of FV to reduce caries incidence in preschoolers.

DESIGN

We included full economic evaluations with preschool participants, in which the intervention was FV and the outcome was related to dentin caries. We searched in CENTRAL; MEDLINE via PubMed; WEB OF SCIENCE; EMBASE; SCOPUS; LILACS; BBO; and BVS Economia em saúde, OpenGrey, and EconoLit. Clinical trial registers, thesis and dissertations, and meeting abstracts were hand searched, as well as 11 dental journals. Risk of bias in the included studies was assessed using the Philips' and Drummond's (full and simplified) tools.

RESULTS

Titles and abstracts of 2871 articles were evaluated, and 200 were read in full. Eight cost-effectiveness studies were included: five modeling and three within-trial evaluations. None of the studies gave sufficient information to allow a thorough assessment using the bias tools. We did not combine the results of the studies due to the great heterogeneity among them. Four studies reported that FV in preschool children was a cost-effective measure, but in one of these studies, sealants and fluoride toothpaste were more cost-effective measures than the varnish, and three studies used limited data that compromised the generalizability of their results. The other four studies showed a large increase in costs due to the application of varnish and/or low cost-effectiveness.

CONCLUSION

We did not find convincing overall evidence that applying FV in preschoolers is an anticaries cost-effective measure. The protocol of this systematic review is available at Open Science Framework (https://osf.io/xw5va/).

Estimating the causal effect of liability to disease on healthcare costs using Mendelian Randomization

Accurate measurement of the effects of disease status on healthcare costs is important in the pragmatic evaluation of interventions but is complicated by endogeneity bias. Mendelian Randomization, the use of random perturbations in germline genetic variation as instrumental variables, can avoid these limitations. We used a novel Mendelian Randomization analysis to model the causal impact on inpatient hospital costs of liability to six prevalent diseases and health conditions: asthma, eczema, migraine, coronary heart disease, Type 2 diabetes, and depression. We identified genetic variants from replicated genome-wide associations studies and estimated their association with inpatient hospital costs on over 300,000 individuals. There was concordance of findings across varieties of sensitivity analyses, including stratification by sex and methods robust to violations of the exclusion restriction. Results overall were imprecise and we could not rule out large effects of liability to disease on healthcare costs. In particular, genetic liability to coronary heart disease had substantial impacts on costs.

Cost-effectiveness of a dietary and physical activity intervention in adolescents: a prototype modelling study based on the Engaging Adolescents in Changing Behaviour (EACH-B) programme

Objective

To assess costs, health outcomes and cost-effectiveness of interventions that aim to improve quality of diet and level of physical activity in adolescents.

Design

A Markov model was developed to assess four potential benefits of healthy behaviour for adolescents: better mental health (episodes of depression and generalised anxiety disorder), higher earnings and reduced incidence of type 2 diabetes and adverse pregnancy outcomes (in terms of preterm delivery). The model parameters were informed by published literature. The analysis took a societal perspective over a 20-year period. One-way and probabilistic sensitivity analyses for 10 000 simulations were conducted.

Participants

A hypothetical cohort of 100 adolescents with a mean age of 13 years.

Interventions

An exemplar school-based, multicomponent intervention that was developed by the Engaging Adolescents for Changing Behaviour programme, compared with usual schooling.

Outcome measure

Incremental cost-effectiveness ratio (ICER) as measured by cost per quality-adjusted life-year (QALY) gained.

Results

The exemplar dietary and physical activity intervention was associated with an incremental cost of £123 per adolescent and better health outcomes with a mean QALY gain of 0.0085 compared with usual schooling, resulting in an ICER of £14 367 per QALY. The key model drivers are the intervention effect on levels of physical activity, quality-of-life gain for high levels of physical activity, the duration of the intervention effects and the period over which effects wane.

Conclusions

The results suggested that such an intervention has the potential to offer a cost-effective use of healthcare-resources for adolescents in the UK at a willingness-to-pay threshold of £20 000 per QALY. The model focused on short-term to medium-term benefits of healthy eating and physical activity exploiting the strong evidence base that exists for this age group. Other benefits in later life, such as reduced cardiovascular risk, are more sensitive to assumptions about the persistence of behavioural change and discounting.

Trail registration number

ISRCTN74109264.

Cost-Utility Analysis of STN1013001, a Latanoprost Cationic Emulsion, versus Other Latanoprost Formulations (Latanoprost) in Open-Angle Glaucoma or Ocular Hypertension and Ocular Surface Disease in France

Purpose

To investigate the cost utility of STN1013001, a latanoprost cationic emulsion, versus Latanoprost in patients with open-angle glaucoma or ocular hypertension (OAG/OHT) and concomitant ocular surface disease (OSD) in France.

Methods

An early Markov model, including 7 health states and a 1-year cycle length, was developed to estimate the cost utility of STN1013001 versus Latanoprost from the French health system perspective over a 5-year time horizon. The model was populated with pooled data (treatment adherence, quality of life, disease progression, and resource utilization) collected, via a questionnaire, from a convenience sample of 5 French glaucoma specialists. Remaining data were retrieved from published sources. Half-cycle correction and 2.5% real social discount rate were applied to costs (in €2020), life years saved (LYS), and quality-adjusted life years (QALYs). The incremental cost-utility ratio (ICUR) was contrasted against the informal willingness-to-pay (WTP) range for incremental LYS or QALY gained (€30,000–€50,000) suggested for France. One-way and probabilistic sensitivity analyses tested the robustness of the baseline ICUR.

Results

Over a 5-year time horizon, STN1013001 resulted in an incremental 0.35 QALYs gained at an incremental cost of €7.39 compared to Latanoprost, resulting in an ICUR of €21.26. This is well below the lower limit of the unofficial WTP range proposed for France. Sensitivity analyses confirmed the robustness of the baseline results.

Conclusion

Once on the market, STN1013001 will provide the French health system with a cost-effective treatment versus Latanoprost for OAG/OHT + OSD patients. These results should be confirmed by future economic evaluations carried out alongside empirical trials.

Uncertainty and the Value of Information in Risk Prediction Modeling

Background

Because of the finite size of the development sample, predicted probabilities from a risk prediction model are inevitably uncertain. We apply value-of-information methodology to evaluate the decision-theoretic implications of prediction uncertainty.

Methods

Adopting a Bayesian perspective, we extend the definition of the expected value of perfect information (EVPI) from decision analysis to net benefit calculations in risk prediction. In the context of model development, EVPI is the expected gain in net benefit by using the correct predictions as opposed to predictions from a proposed model. We suggest bootstrap methods for sampling from the posterior distribution of predictions for EVPI calculation using Monte Carlo simulations. We used subsets of data of various sizes from a clinical trial for predicting mortality after myocardial infarction to show how EVPI changes with sample size.

Results

With a sample size of 1000 and at the prespecified threshold of 2% on predicted risks, the gains in net benefit using the proposed and the correct models were 0.0006 and 0.0011, respectively, resulting in an EVPI of 0.0005 and a relative EVPI of 87%. EVPI was zero only at unrealistically high thresholds (>85%). As expected, EVPI declined with larger samples. We summarize an algorithm for incorporating EVPI calculations into the commonly used bootstrap method for optimism correction.

Conclusion

The development EVPI can be used to decide whether a model can advance to validation, whether it should be abandoned, or whether a larger development sample is needed. Value-of-information methods can be applied to explore decision-theoretic consequences of uncertainty in risk prediction and can complement inferential methods in predictive analytics. R code for implementing this method is provided.

Cost–Utility Analysis of a Latanoprost Cationic Emulsion (STN1013001) versus Other Latanoprost in the Treatment of Open-Angle Glaucoma or Ocular Hypertension and Concomitant Ocular Surface Disease in Germany

Purpose

This study aimed to estimate the cost–utility and economic value of STN1013001, a latanoprost cationic emulsion vs other latanoprost formulations (henceforth latanoprost) in patients with open-angle glaucoma (OAG) or ocular hypertension (OHT) and concomitant ocular surface disease (OSD) in Germany.

Methods

An early 5-year Markov model-supported cost–utility analysis was performed to estimate costs, quality-adjusted life years (QALYs) and life-years saved (LYS) for STN1013001 vs latanoprost from the German health system perspective. The model included seven mutually exclusive health states and adopted a 1-year cycle length. The model was populated with pooled data derived, by means of a questionnaire, from a convenience sample of five German glaucoma specialists. Remaining data were derived from published sources. Data provided by the ophthalmologists included annual treatment adherence probabilities, utility values and resource utilization. The half-cycle correction as well as a discount rate of 3.0% per year were applied to costs (expressed in €2020), life-year saved (LYS) and QALYs. The incremental cost–utility ratio (ICUR) was contrasted against the informal willingness-to-pay (WTP) threshold for incremental LYS saved or QALY gained (€30,000) proposed for Germany. One-way and probabilistic sensitivity analyses (OWSA; PSA) tested the robustness of the base case ICUR.

Results

Over the 5-year time horizon, STN1013001 strongly dominates latanoprost as it is less costly (€1003.65 vs €1145.37; −12.37%) and produces more QALYs (2.612 vs 2.365; +10.44%) per notional patient. Baseline findings were robust against all the variations included in OWSA. PSA shows that STN1013001 has a 100% probability of being cost-effective vs Latanoprost at each WTP threshold for incremental QALY gained.

Conclusion

Once on the market, STN1013001 will provide a cost-effective and possibly strongly dominant therapy vs latanoprost for OAG/OHT+OSD patients from a German health system perspective. Future empirical research should confirm these findings.

Development and validation of the risk engine for an Australian Health Economics Model of Osteoporosis

The Australian Health Economics Model of Osteoporosis (AusHEMO) has shown good face, internal and cross validities, and can be used to assist healthcare decision-making in Australia.

PURPOSE

This study aimed to document and validate the risk engine of the Australian Health Economics Model of Osteoporosis (AusHEMO).

METHODS

AusHEMO is a state-transition microsimulation model. The fracture risks were simulated using fracture incidence rates from the Dubbo Osteoporosis Epidemiology Study. The AusHEMO was validated regarding its face, internal and cross validities. Goodness-of-fit analysis was conducted and Lin's coefficient of agreement and mean absolute difference with 95% limits of agreement were reported.

RESULTS

The development of AusHEMO followed general and osteoporosis-specific health economics guidelines. AusHEMO showed good face validity regarding the model's structure, evidence, problem formulation and results. In addition, the model has been proven good internal and cross validities in goodness-of-fit test. Lin's coefficient was 0.99, 1 and 0.94 for validation against the fracture incidence rates, Australian life expectancies and residual lifetime fracture risks, respectively.

CONCLUSIONS

In summary, the development of the risk engine of AusHEMO followed the best practice for osteoporosis disease modelling and the model has been shown to have good face, internal and cross validities. The AusHEMO can be confidently used to predict long-term fracture-related outcomes and health economic evaluations when costs data are included. Health policy-makers in Australia can use the AusHEMO to select which osteoporosis interventions such as medications and public health interventions represent good value for money.

Modeling Early Warning Systems: Construction and Validation of a Discrete Event Simulation Model for Heart Failure

OBJECTIVES

Developing and validating a discrete event simulation model that is able to model patients with heart failure managed with usual care or an early warning system (with or without a diagnostic algorithm) and to account for the impact of individual patient characteristics in their health outcomes.

METHODS

The model was developed using patient-level data from the Trans-European Network - Home-Care Management System study. It was coded using RStudio Version 1.3.1093 (version 3.6.2.) and validated along the lines of the Assessment of the Validation Status of Health-Economic decision models tool. The model includes 20 patient and disease characteristics and generates 8 different outcomes. Model outcomes were generated for the base-case analysis and used in the model validation.

RESULTS

Patients managed with the early warning system, compared with usual care, experienced an average increase of 2.99 outpatient visits and a decrease of 0.02 hospitalizations per year, with a gain of 0.81 life years (0.45 quality-adjusted life years) and increased average total costs of €11 249. Adding a diagnostic algorithm to the early warning system resulted in a 0.92 life year gain (0.57 quality-adjusted life years) and increased average costs of €9680. These patients experienced a decrease of 0.02 outpatient visits and 0.65 hospitalizations per year, while they avoided being hospitalized 0.93 times. The model showed robustness and validity of generated outcomes when comparing them with other models addressing the same problem and with external data.

CONCLUSIONS

This study developed and validated a unique patient-level simulation model that can be used for simulating a wide range of outcomes for different patient subgroups and treatment scenarios. It provides useful information for guiding research and for developing new treatment options by showing the hypothetical impact of these interventions on a large number of important heart failure outcomes.

Estimation of Transition Probabilities for State-Transition Models: A Review of NICE Appraisals

State transition models are used to inform health technology reimbursement decisions. Within state transition models, the movement of patients between the model health states over discrete time intervals is determined by transition probabilities (TPs). Estimating TPs presents numerous issues, including missing data for specific transitions, data incongruence and uncertainty around extrapolation. Inappropriately estimated TPs could result in biased models. There is limited guidance on how to address common issues associated with TP estimation. To assess current methods for estimating TPs and to identify issues that may introduce bias, we reviewed National Institute for Health and Care Excellence Technology Appraisals published from 1 January, 2019 to 27 May, 2020. Twenty-eight models (from 26 Technology Appraisals) were included in the review. Several methods for estimating TPs were identified: survival analysis (n = 11); count method (n = 9); multi-state modelling (n = 7); logistic regression (n = 2); negative binomial regression (n = 2); Poisson regression (n = 1); and calibration (n = 1). Evidence Review Groups identified several issues relating to TP estimation within these models, including important transitions being excluded (n = 5); potential selection bias when estimating TPs for post-randomisation health states (n = 2); issues concerning the use of multiple data sources (n = 4); potential biases resulting from the use of data from different populations (n = 2), and inappropriate assumptions around extrapolation (n = 3). These issues remained unresolved in almost every instance. Failing to address these issues may bias model results and lead to sub-optimal decision making. Further research is recommended to address these methodological problems.

Real-World Cost-Effectiveness of Bevacizumab With First-Line Combination Chemotherapy in Patients With Metastatic Colorectal Cancer: Population-Based Retrospective Cohort Studies in Three Canadian Provinces

Background. Real-world evidence can be a valuable tool when clinical trial data are incomplete or uncertain. Bevacizumab was adopted as first-line therapy for metastatic colorectal cancer (mCRC) based on significant survival improvements in initial clinical trials; however, survival benefit diminished in subsequent analyses. Consequently, there is uncertainty surrounding the cost-effectiveness of bevacizumab therapy achieved in practice. Objective. To assess real-world cost-effectiveness of first-line bevacizumab with irinotecan-based chemotherapy versus irinotecan-based chemotherapy alone for mCRC in British Columbia (BC), Saskatchewan, and Ontario, Canada. Methods. Using provincial cancer registries and linked administrative databases, we identified mCRC patients who initiated publicly funded irinotecan-based chemotherapy, with or without bevacizumab, in 2000 to 2015. We compared bevacizumab-treated patients to historical controls (treated before bevacizumab funding) and contemporaneous controls (receiving chemotherapy without bevacizumab), using inverse-probability-of-treatment weighting with propensity scores to balance baseline covariates. We calculated incremental cost-effectiveness ratios (ICER) using 5-year cost and survival adjusted for censoring, with bootstrapping to characterize uncertainty. We also conducted one-way sensitivity analysis for key drivers of cost-effectiveness. Results. The cohorts included 12,112 (Ontario), 1,161 (Saskatchewan), and 2,977 (BC) patients. Bevacizumab significantly increased treatment costs, with mean ICERs between $78,000 and $84,000/LYG (life-year gained) in the contemporaneous comparisons and $75,000 and $101,000/LYG in the historical comparisons. Reducing the cost of bevacizumab by 50% brought ICERs in all comparisons below $61,000/LYG. Limitations. Residual confounding in observational data may bias results, while the use of original list prices overestimates current bevacizumab cost. Conclusion. The addition of bevacizumab to irinotecan-based chemotherapy extended survival for mCRC patients but at significant cost. At original list prices bevacizumab can only be considered cost-effective with certainty at a willingness-to-pay threshold over $100,000/LYG, but price reductions or discounts have a significant impact on cost-effectiveness.

Occipital Nerve Stimulation for Refractory Chronic Cluster Headache: A Cost-Effectiveness Study

INTRODUCTION

Occipital nerve stimulation (ONS) is proposed to treat refractory chronic cluster headache (rCCH), but its cost-effectiveness has not been evaluated, limiting its diffusion and reimbursement.

MATERIALS AND METHODS

We performed a before-and-after economic study, from data collected prospectively in a nation-wide registry. We compared the cost-effectiveness of ONS associated with conventional treatment (intervention and postintervention period) to conventional treatment alone (preintervention period) in the same patients. The analysis was conducted on 76 rCCH patients from the French healthcare perspective at three months, then one year by extrapolation. Because of the impact of the disease on patient activity, indirect cost, such as sick leave and disability leave, was assessed second.

RESULTS

The average total cost for three months was €7602 higher for the ONS strategy compared to conventional strategy with a gain of 0.07 quality-adjusted life-years (QALY), the incremental cost-effectiveness ratio (ICER) was then €109,676/QALY gained. The average extrapolated total cost for one year was €1344 lower for the ONS strategy (p = 0.5444) with a gain of 0.28 QALY (p < 0.0001), the ICER was then €-4846/QALY gained. The scatter plot of the probabilistic bootstrapping had 80% of the replications in the bottom right-hand quadrant, indicating that the ONS strategy is dominant. The average indirect cost for three months was €377 lower for the ONS strategy (p = 0.1261).

DISCUSSION

This ONS cost-effectiveness study highlighted the limitations of a short-time horizon in an economic study that may lead the healthcare authorities to reject an innovative strategy, which is actually cost-effective. One-year extrapolation was the proposed solution to obtain results on which healthcare authorities can base their decisions.

CONCLUSION

Considering the burden of rCCH and the efficacy and safety of ONS, the demonstration that ONS is dominant should help its diffusion, validation, and reimbursement by health authorities in this severely disabled population.

Physical Activity Interventions for Primary Prevention in Adults: A Systematic Review of Randomized Controlled Trial-Based Economic Evaluations

BACKGROUND

Physical inactivity is a worldwide pandemic associated with major chronic diseases. Given limited resources, policy makers are in need of physical activity interventions that provide best value for money.

OBJECTIVE

To summarize evidence from RCT-based economic evaluations of primary prevention physical activity interventions in adult populations outside the workplace setting.

DESIGN

Systematic review of health economic evaluations. Incremental cost-effectiveness ratios (ICERs) in US$ per MET-hour gained were estimated on the basis of mean differences in intervention costs and standardized effects between intervention and control groups.

DATA SOURCES

Identification of relevant studies via systematic searches in electronic databases (MEDLINE, Embase and NHSEED).

ELIGIBILITY CRITERIA

Cost-effectiveness analyses in which all data (except unit costs) came from one RCT investigating physical activity interventions for primary prevention or health promotion in an adult population in high-income countries.

RESULTS

In twelve eligible studies, 22 interventions were investigated. Interventions were based on advice, goal setting and follow-up support, exercise classes, financial incentives or teaching on behavioral change. The ICER varied widely among the interventions and four interventions showed an ICER below the applied benchmark of US$0.44 to US$0.63 per MET-hour gained. These four interventions were based on individualized advice via print or web.

CONCLUSION

We found evidence from RCTs indicating cost-effectiveness of some physical activity interventions for primary prevention in adults. However, the majority of interventions assessed would not be cost-effective according to the benchmark applied. Furthermore, our study showed that trial-based evidence on cost-effectiveness of physical activity interventions is scarce. Therefore, we recommend that future studies investigating the efficacy or effectiveness of such interventions consider costs as an additional outcome and assess cost-effectiveness.

Unbiasing costs? An appraisal of economic assessment alongside randomized trials in neonatology

Economic evaluations performed alongside randomized controlled trials benefit from the protections against bias inherent in randomization. In this systematic review, we assessed the frequency and quality of economic assessments alongside randomized controlled trials of interventions in neonates published between 1990 and 2016. Over that period, 58 economic assessments were published, corresponding to approximately 2% of RCTs. We noted significant methodological limitations of these studies, including limitation of included costs to the health sector or payer rather than broader categories such as family or community expenditures (81%), short time horizon for cost measurement (less than one year in 60%), lack of reporting of uncertainty (26%), and infrequent analysis of costs and effects in a single metric (combined in 45%). Strategies for improving the quality and frequency of economic evaluations in neonatology are discussed, including selection of appropriate trials, funding, and peer review.

Summary of Proceedings and Expert Consensus Statements From the International Summit "Lipids in Parenteral Nutrition"

BACKGROUND

The 2018 Lipids in Parenteral Nutrition summit involved a panel of experts in clinical nutrition, lipid metabolism, and pharmacology, to assess the current state of knowledge and develop expert consensus statements regarding the use of intravenous lipid emulsions in various patient populations and clinical settings. The main purpose of the consensus statements is to assist healthcare professionals by providing practical guidance on common clinical questions related to the provision of lipid emulsions as part of parenteral nutrition (PN).

METHODS

The summit was designed to allow interactive discussion and consensus development. The resulting consensus statements represent the collective opinion of the members of the expert panel, which was informed and supported by scientific evidence and clinical experience.

RESULTS

The current article summarizes the key discussion topics from the summit and provides a set of consensus statements designed to complement existing evidence-based guidelines. Lipid emulsions are a major component of PN, serving as a condensed source of energy and essential fatty acids. In addition, lipids modulate a variety of biologic functions, including inflammatory and immune responses, coagulation, and cell signaling. A growing body of evidence suggests that lipid emulsions containing ω-3 fatty acids from fish oil confer important clinical benefits via suppression of inflammatory mediators and activation of pathways involved in the resolution of inflammation.

CONCLUSIONS

This article provides a set of expert consensus statements to complement formal PN guideline recommendations.

Prevalence and medical expenditures of diabetes-related complications among adult Medicaid enrollees with diabetes in eight U.S. states

AIMS

To estimate the prevalence and medical expenditures of diabetes-related complications (DRCs) among adult Medicaid enrollees with diabetes.

METHODS

We estimated the prevalence and medical expenditures for 12 diabetes-related complications by Medicaid eligibility category (disability-based vs. non-disability-based) in eight states. We used generalized linear models with log link and gamma distribution to estimate the total per-person annual medical expenditures for DRCs, controlling for demographics, and other comorbidities.

RESULTS

Among non-disability-based enrollees (NDBEs), 40.1% (in California) to 47.5% (in Oklahoma) had one or more DRCs, compared to 53.6% (in Alabama) to 64.8% (in Florida) among disability-based enrollees (DBEs). The most prevalent complication was neuropathy (16.1%-27.1% for NDBEs; 20.2%-30.4% for DBEs). Lower extremity amputation (<1% for both eligibilities) was the least prevalent complication. The costliest per-person complication was dialysis (per-person excess annual expenditure of $22,481-$41,298 for NDBEs; $23,569-$51,470 for DBEs in 2012 USD). Combining prevalence and per-person excess expenditures, the three costliest complications were nephropathy, heart failure, and ischemic heart disease (IHD) for DBEs, compared to neuropathy, nephropathy, and IHD for NDBEs.

CONCLUSIONS

Our study provides data that can be used for assessing the health care resources needed for managing DRCs and evaluating cost-effectiveness of interventions to prevent and management DRCs.

Using Metamodeling to Identify the Optimal Strategy for Colorectal Cancer Screening

OBJECTIVES

Metamodeling can address computational challenges within decision-analytic modeling studies evaluating many strategies. This article illustrates the value of metamodeling for evaluating colorectal cancer screening strategies while accounting for colonoscopy capacity constraints.

METHODS

In a traditional approach, the best screening strategy was identified from a limited subset of strategies evaluated with the validated Adenoma and Serrated pathway to Colorectal CAncer model. In a metamodeling approach, metamodels were fitted to this limited subset to evaluate all potentially plausible strategies and determine the best overall screening strategy. Approaches were compared based on the best screening strategy in life-years gained compared with no screening. Metamodel runtime and accuracy was assessed.

RESULTS

The metamodeling approach evaluated >40 000 strategies in <1 minute with high accuracy after 1 adaptive sampling step (mean absolute error: 0.0002 life-years) using 300 samples in total (generation time: 8 days). Findings indicated that health outcomes could be improved without requiring additional colonoscopy capacity. Obtaining similar insights using the traditional approach could require at least 1000 samples (generation time: 28 days). Suggested benefits from screening at ages <40 years require adequate validation of the underlying Adenoma and Serrated pathway to Colorectal CAncer model before making policy recommendations.

CONCLUSIONS

Metamodeling allows rapid assessment of a vast set of strategies, which may lead to identification of more favorable strategies compared to a traditional approach. Nevertheless, metamodel validation and identifying extrapolation beyond the support of the original decision-analytic model are critical to the interpretation of results. The screening strategies identified with metamodeling support ongoing discussions on decreasing the starting age of colorectal cancer screening.

Feasibility analysis of a prevention programme for patients with early chronic disease using A mathematical model

The increasing prevalence of the chronic disease is of considerable concern to health-care organisations. Prevention programmes to patients with early chronic disease have the potential to improve individual health and quality of life through disease avoidance or delay and to save the medical cost of the health care system. Due to the limited budget in healthcare this study seeks to analyse the feasibility of a programme prior to implementation. A mathematical model is developed to determine incidence reduction rate at which the underlying cost break-even can be achieved; consequently, the programme would be feasible. We show the existence and uniqueness of the underlying incidence reduction and establish the feasibility frontier concerning the trade-offs between intervention effective period and incidence reduction rate. We use a diabetes prevention programme to demonstrate the efficiency and advantage of the model. The proposed model would inform decision-makers scientific principles in determining an intervention for implementation.

Systematic Review of Health State Utility Values Used in European Pharmacoeconomic Evaluations for Chronic Hepatitis C: Impact on Cost-Effectiveness Results

BACKGROUND

Health state utility values (HSUVs) identified from utility elicitation studies are widely used in pharmacoeconomic evaluations for chronic hepatitis C (CHC) and are particularly instrumental in health technology assessment (HTA) evaluations such as those from the National Institute for Health and Care Excellence (NICE).

OBJECTIVE

The aim of this study was to identify HSUVs used in cost-utility analyses (CUAs) for CHC in Europe and to evaluate the impact of HSUV selection on cost-effectiveness results in terms of the incremental cost per quality-adjusted life-year (QALY) gained (ICER).

METHODS

A systematic search of pharmacoeconomic evaluations for CHC was updated in the MEDLINE and EMBASE databases for the periods 2012-2017 and 2017-2020. Data on health states, HSUVs, and utility elicitation studies were extracted. The difference in HSUVs of the same health state in different CUAs, and the difference between HSUVs of one health state and of the interlink health state in the same CUAs, were calculated. A quality assessment was performed to evaluate the selection of HSUVs in CUAs. Sets of HSUVs identified were used in a reconstructed CUA model to assess the impact on the ICER.

RESULTS

Twenty-six CUAs conducted in European countries and referring to 17 utility elicitation studies were included. The difference in HSUVs of the same health state in different CUAs ranged from 0.021 (liver transplant) to 0.468 (decompensated cirrhosis). The difference between HSUVs of one health state and of the interlink health state of the next disease severity level was calculated between the health states of F0-F1/mild and F2-F3/moderate (n = 11, 0.040-0.110), F2-F3/moderate and F4/compensated cirrhosis (n = 18, 0.027-0.130), compensated cirrhosis and decompensated cirrhosis (n = 22, 0.020-0.100), decompensated cirrhosis and hepatocellular carcinoma (n = 24, 0.000-0.200), hepatocellular carcinoma and liver transplant in the first year (n = 17, - 0.329 to 0.170) and liver transplant in the first and subsequent years (n = 17, - 0.340 to 0.000). The utility elicitation study selected by most CUAs (n = 11) was recommended as the source of HSUVs, at least for the CUAs conducted in the UK, based on the results of quality assessment. Seven sets of HSUVs were generated to fit the reconstructed model and changed the results of the incremental analysis from being cost effective to not being cost effective (ICER ranging from £2460 to £24,954 per QALY gained), and to being dominated in the UK setting.

CONCLUSIONS

The CUAs for CHC were found to apply to various HSUVs from different utility elicitation studies in the same health state. This variability in HSUVs has the potential to significantly affect ICER and ICER-based reimbursement decisions. A rigorous selection of HSUVs in CUAs to inform healthcare resource allocation is suggested for future studies of CUAs and for guideline development.

Health economic design for cost, cost-effectiveness and simulation analyses in the HEALing Communities Study

BACKGROUND

The HEALing Communities Study (HCS) is designed to implement and evaluate the Communities That HEAL (CTH) intervention, a conceptually driven framework to assist communities in selecting and adopting evidence-based practices to reduce opioid overdose deaths. The goal of the HCS is to produce generalizable information for policy makers and community stakeholders seeking to implement CTH or a similar community intervention. To support this objective, one aim of the HCS is a health economics study (HES), the results of which will inform decisions around fiscal feasibility and sustainability relevant to other community settings.

METHODS

The HES is integrated into the HCS design: an unblinded, multisite, parallel arm, cluster randomized, wait list-controlled trial of the CTH intervention implemented in 67 communities in four U.S. states: Kentucky, Massachusetts, New York, and Ohio. The objectives of the HES are to estimate the economic costs to communities of implementing and sustaining CTH; estimate broader societal costs associated with CTH; estimate the cost-effectiveness of CTH for overdose deaths avoided; and use simulation modeling to evaluate the short- and long-term health and economic impact of CTH, including future overdose deaths avoided and quality-adjusted life years saved, and to develop a simulation policy tool for communities that seek to implement CTH or a similar community intervention.

DISCUSSION

The HCS offers an unprecedented opportunity to conduct health economics research on solutions to the opioid crisis and to increase understanding of the impact and value of complex, community-level interventions.

Evaluating the Ability of Economic Models of Diabetes to Simulate New Cardiovascular Outcomes Trials: A Report on the Ninth Mount Hood Diabetes Challenge

OBJECTIVES

The cardiovascular outcomes challenge examined the predictive accuracy of 10 diabetes models in estimating hard outcomes in 2 recent cardiovascular outcomes trials (CVOTs) and whether recalibration can be used to improve replication.

METHODS

Participating groups were asked to reproduce the results of the Empagliflozin Cardiovascular Outcome Event Trial in Type 2 Diabetes Mellitus Patients (EMPA-REG OUTCOME) and the Canagliflozin Cardiovascular Assessment Study (CANVAS) Program. Calibration was performed and additional analyses assessed model ability to replicate absolute event rates, hazard ratios (HRs), and the generalizability of calibration across CVOTs within a drug class.

RESULTS

Ten groups submitted results. Models underestimated treatment effects (ie, HRs) using uncalibrated models for both trials. Calibration to the placebo arm of EMPA-REG OUTCOME greatly improved the prediction of event rates in the placebo, but less so in the active comparator arm. Calibrating to both arms of EMPA-REG OUTCOME individually enabled replication of the observed outcomes. Using EMPA-REG OUTCOME-calibrated models to predict CANVAS Program outcomes was an improvement over uncalibrated models but failed to capture treatment effects adequately. Applying canagliflozin HRs directly provided the best fit.

CONCLUSIONS

The Ninth Mount Hood Diabetes Challenge demonstrated that commonly used risk equations were generally unable to capture recent CVOT treatment effects but that calibration of the risk equations can improve predictive accuracy. Although calibration serves as a practical approach to improve predictive accuracy for CVOT outcomes, it does not extrapolate generally to other settings, time horizons, and comparators. New methods and/or new risk equations for capturing these CV benefits are needed.

Economic Evaluation of Interventions to Address Opioid Misuse: A Systematic Review of Methods Used in Simulation Modeling Studies

OBJECTIVES

Several evidence-based interventions exist for people who misuse opioids, but there is limited guidance on optimal intervention selection. Economic evaluations using simulation modeling can guide the allocation of resources and help tackle the opioid crisis. This study reviews methods employed by economic evaluations using computer simulations to investigate the health and economic effects of interventions meant to address opioid misuse.

METHODS

We conducted a systematic mapping review of studies that used simulation modeling to support the economic evaluation of interventions targeting prevention, treatment, or management of opioid misuse or its direct consequences (ie, overdose). We searched 6 databases and extracted information on study population, interventions, costs, outcomes, and economic analysis and modeling approaches.

RESULTS

Eighteen studies met the inclusion criteria. All of the studies considered only one segment of the continuum of care. Of the studies, 13 evaluated medications for opioid use disorder, and 5 evaluated naloxone distribution programs to reduce overdose deaths. Most studies estimated incremental cost per quality-adjusted life-years and used health system and/or societal perspectives. Models were decision trees (n = 4), Markov (n = 10) or semi-Markov models (n = 3), and microsimulations (n = 1). All of the studies assessed parameter uncertainty though deterministic and/or probabilistic sensitivity analysis, 4 conducted formal calibration, only 2 assessed structural uncertainty, and only 1 conducted expected value of information analyses. Only 10 studies conducted validation.

CONCLUSIONS

Future economic evaluations should consider synergies between interventions and examine combinations of interventions to inform optimal policy response. They should also more consistently conduct model validation and assess the value of further research.

Economic Evaluation Studies

Economic evaluations, including cost-effectiveness analyses, are frameworks for decision-making. They help to illustrate tradeoffs between selecting one choice over another. This form of analysis is of great power and value to the health-care system. Health-care decisions are complex; they require synthesis of a myriad of data variables and sources, and the impact of the choices made is significant. Given this importance and the increasing demand and complexity of health decisions, it is imperative to ensure that economic evaluations are of high quality, comprehensive, and follow the guidelines and recommendations of experts in the field. This article provides an overview of the types of economic evaluations and their role in decision-making. It also discusses key study design considerations, including methods, scope, results, and reporting. Links to published checklists are provided along with additional sources of information, including a glossary of terms (Appendix), to guide the researcher to produce high-quality economic evaluations and guide the reviewer to provide high-quality feedback during the review process.

Systematic review of the methods of health economic models assessing antipsychotic medication for schizophrenia

BACKGROUND

Numerous economic models have assessed the cost-effectiveness of antipsychotic medications in schizophrenia. It is important to understand what key impacts of antipsychotic medications were considered in the existing models and limitations of existing models in order to inform the development of future models.

OBJECTIVES

This systematic review aims to identify which clinical benefits, clinical harms, costs and cost savings of antipsychotic medication have been considered by existing models, to assess quality of existing models and to suggest good practice recommendations for future economic models of antipsychotic medications.

METHODS

An electronic search was performed on multiple databases (MEDLINE, EMBASE, PsycInfo, Cochrane database of systematic reviews, The NHS Economic Evaluation Database and Health Technology Assessment database) to identify economic models of schizophrenia published between 2005-2020. Two independent reviewers selected studies for inclusion. Study quality was assessed using the National Institute for Health and Care Excellence (NICE) checklist and the Cooper hierarchy. Key impacts of antipsychotic medications considered by exiting models were descriptively summarised.

RESULTS

Sixty models were included. Existing models varied greatly in key impacts of antipsychotic medication included in the model, especially in clinical outcomes used for assessing reduction in psychotic symptoms and types of adverse events considered in the model. Quality of existing models was generally low due to failure to capture the health and cost impact of adverse events of antipsychotic medications and input data not obtained from best available source. Good practices for modelling antipsychotic medications are suggested.

DISCUSSIONS

This review highlights inconsistency in key impacts considered by different models, and limitations of the existing models. Recommendations on future research are provided.

What are the benefits and harms of risk stratified screening as part of the NHS breast screening Programme? Study protocol for a multi-site non-randomised comparison of BC-predict versus usual screening (NCT04359420)

BACKGROUND

In principle, risk-stratification as a routine part of the NHS Breast Screening Programme (NHSBSP) should produce a better balance of benefits and harms. The main benefit is the offer of NICE-approved more frequent screening and/ or chemoprevention for women who are at increased risk, but are unaware of this. We have developed BC-Predict, to be offered to women when invited to NHSBSP which collects information on risk factors (self-reported information on family history and hormone-related factors via questionnaire; mammographic density; and in a sub-sample, Single Nucleotide Polymorphisms). BC-Predict produces risk feedback letters, inviting women at high risk (≥8% 10-year) or moderate risk (≥5 to < 8% 10-year) to have discussion of prevention and early detection options at Family History, Risk and Prevention Clinics. Despite the promise of systems such as BC-Predict, there are still too many uncertainties for a fully-powered definitive trial to be appropriate or ethical. The present research aims to identify these key uncertainties regarding the feasibility of integrating BC-Predict into the NHSBSP. Key objectives of the present research are to quantify important potential benefits and harms, and identify key drivers of the relative cost-effectiveness of embedding BC-Predict into NHSBSP.

METHODS

A non-randomised fully counterbalanced study design will be used, to include approximately equal numbers of women offered NHSBSP (n = 18,700) and BC-Predict (n = 18,700) from selected screening sites (n = 7). In the initial 8-month time period, women eligible for NHSBSP will be offered BC-Predict in four screening sites. Three screening sites will offer women usual NHSBSP. In the following 8-months the study sites offering usual NHSBSP switch to BC-Predict and vice versa. Key potential benefits including uptake of risk consultations, chemoprevention and additional screening will be obtained for both groups. Key potential harms such as increased anxiety will be obtained via self-report questionnaires, with embedded qualitative process analysis. A decision-analytic model-based cost-effectiveness analysis will identify the key uncertainties underpinning the relative cost-effectiveness of embedding BC-Predict into NHSBSP.

DISCUSSION

We will assess the feasibility of integrating BC-Predict into the NHSBSP, and identify the main uncertainties for a definitive evaluation of the clinical and cost-effectiveness of BC-Predict.

TRIAL REGISTRATION

Retrospectively registered with clinicaltrials.gov (NCT04359420).

Addressing Challenges of Economic Evaluation in Precision Medicine Using Dynamic Simulation Modeling

OBJECTIVES

The objective of this article is to describe the unique challenges and present potential solutions and approaches for economic evaluations of precision medicine (PM) interventions using simulation modeling methods.

METHODS

Given the large and growing number of PM interventions and applications, methods are needed for economic evaluation of PM that can handle the complexity of cascading decisions and patient-specific heterogeneity reflected in the myriad testing and treatment pathways. Traditional approaches (eg, Markov models) have limitations, and other modeling techniques may be required to overcome these challenges. Dynamic simulation models, such as discrete event simulation and agent-based models, are used to design and develop mathematical representations of complex systems and intervention scenarios to evaluate the consequence of interventions over time from a systems perspective.

RESULTS

Some of the methodological challenges of modeling PM can be addressed using dynamic simulation models. For example, issues regarding companion diagnostics, combining and sequencing of tests, and diagnostic performance of tests can be addressed by capturing patient-specific pathways in the context of care delivery. Issues regarding patient heterogeneity can be addressed by using patient-level simulation models.

CONCLUSION

The economic evaluation of PM interventions poses unique methodological challenges that might require new solutions. Simulation models are well suited for economic evaluation in PM because they enable patient-level analyses and can capture the dynamics of interventions in complex systems specific to the context of healthcare service delivery.

An analysis of the effectiveness outcomes of economic studies evaluating ophthalmic drugs: a systematic review

PURPOSE

To characterize the effectiveness measures of cost-effectiveness studies (CES) of ophthalmic drugs.

METHODS

A systematic review was conducted in PubMed/Embase until October 2019. Cost-effectiveness studies (CES) evaluating ophthalmic drugs were included. Sources of effectiveness measures were extracted. Data on study design and study outcomes were extracted from sources of effectiveness measures. The adequacy of the sample size of the clinical studies used as sources of effectiveness measures was assessed. If CES have retrieved effectiveness data from multiple sources, the appropriateness of the method to combine the results was analysed.

RESULTS

Forty-five CES were included. Thirty-one (68.9%) retrieved their effectiveness measures from experimental studies, five (11.1%) from observational studies and nine (20%) from other type of data sources. Eight (17.8%) CES used data from a primary outcome of a study as an effectiveness measure, eight (17.8%) used data from secondary outcomes, seven (15.6%) used data from the both primary and secondary outcomes and for 22 (48.9%) it was not possible to identify the outcomes used. From the 23 (51.1%) CES based on a single clinical study, three (6.7%) included data from clinical studies which had an adequate sample size to detect significant differences in the clinical outcomes used as effectiveness measures. From the 17 (37.8%) CES based on multiple clinical studies, only one (2.2%) used and/or reported an adequate method of quantitative synthesis (meta-analysis).

CONCLUSION

A considerable number of CES in ophthalmology were not based on clinical studies with adequate sample sizes and report results from effectiveness measures not assessed as primary outcomes.

The integrated care pathway for managing post stroke patients (iCaPPS©) in public primary care Healthcentres in Malaysia: impact on quality adjusted life years (QALYs) and cost effectiveness analysis

Background

The delivery of post stroke care is fragmented even in advanced public healthcare systems, globally. Primary care teams are entrusted to provide longer term care for stroke survivors in most developing countries. The integrated Care Pathway for Post Stroke patients (iCaPPS^©) was designed to guide primary care teams to incorporate further rehabilitation and regular screening for post stroke complications among patients residing at home in communities, using the shared-care approach, especially in areas with limited access to specialist stroke care services. The iCaPPS^© addressed coordination of rehabilitation and screening for post stroke complications which were absent in the current conventional care of patients managed at public primary care healthcentres. This study aimed to evaluate the cost effectiveness and impact of iCaPPS^© on quality-adjusted- life-years (QALY) compared with current conventional monitoring at public primary care healthcentres.

Methods

A pragmatic healthcentre-based cluster randomised controlled trial-within trial on 151 post stroke patients from 10 public primary care facilities in Peninsular Malaysia was conducted to evaluate QALY of patients managed with iCaPPS^© (n = 86) vs conventional care (n = 65) for 6 months. Costs from societal perspective were calculated, using combination of top down and activity-based costing methods. The 5-level EQ5D (EQ-5D-5 L) was used to calculate health state utility scores. Cost per QALY and incremental cost effectiveness ratio (ICER) were determined. Differences within groups were determined using Mann-Whitney tests.

Results

Total costs for 6 months treatment with iCaPPS^© was MYR790.34, while conventional care cost MYR527.22. Median QALY for iCaPPS^© was 0.55 (0,1.65) compared to conventional care 0.32 (0, 0.73) (z = − 0.21, p = 0.84). Cost per QALY for iCaPPS^© was MYR1436.98, conventional care was MYR1647.56. The ICER was MYR1144.00, equivalent to 3.7% of per capita GDP (2012 prices).

Conclusions

Management of post stroke patients in the community using iCaPPS^© costs less per QALY compared to current conventional care and is very cost effective.

Trial registration

Trial Registration number ACTRN12616001322426. Registered 21 September 2016. (Retrospectively registered).

Through the quality kaleidoscope: reflections on research in dentomaxillofacial imaging

The REduce research Waste And Reward Diligence statement has highlighted how weaknesses in health research can produce misleading results and waste valuable resources. Research on diagnostic efficacy in the field of dentomaxillofacial radiology (DMFR) is no exception to these criticisms and could be strengthened by more robust study designs, consistent use of a core set of outcome measures and completeness in reporting. Furthermore, we advocate that everyone participating in collaborative research on clinical interventions subscribes to the importance of methodological quality in how imaging methods are used. The aim of this paper, therefore, is to present a guide to conducting high-quality research on diagnostic efficacy in DMFR.We initially propose a framework inspired by the hierarchical model of efficacy of Fryback and Thornbury, highlighting study designs, measures of analysis, completeness of reporting and established guidelines to assist in these aspects of research. Bias in research, and measures to prevent or limit it, are then described.It is desirable to climb the Fryback and Thornbury "ladder" from technical efficacy, via accuracy and clinical efficacy, to societal efficacy of imaging methods. Efficacy studies on the higher steps of the ladder may be difficult to perform, but we must strive to answer questions of how useful our methods are in patient management and assess benefits, risks, costs, ethical and social issues. With the framework of six efficacy levels as the structure and based on our experience, we present information that may facilitate quality enhancement of diagnostic efficacy research in DMFR.

When and what to test for: A cost-effectiveness analysis of febrile illness test-and-treat strategies in the era of responsible antibiotic use

BACKGROUND

Febrile illness caused by viral and bacterial diseases (e.g., dengue and leptospirosis) often have similar symptoms and are difficult to differentiate without diagnostic tests. If not treated appropriately, patients may experience serious complications. The question of what diagnostic tests to make available to providers in order to inform antibiotic therapy remains an open problem for health services facing limited resources.

METHODS AND FINDINGS

We formulated the problem of minimizing the weighted average of antibiotic underuse and overuse to inform the optimal diagnostic test and antibiotic treatment options for given occurrence probabilities of several bacterial and viral infections. We modeled the weight of antibiotic overuse as a monetary penalty per unnecessarily administered course, which we varied in both the base case and sensitivity analysis. Detailed Markov cohort models of febrile illness progression were used to estimate the weight of antibiotic underuse. The model accounted for multiple infections simultaneously and incorporated test, treatment, and other direct and indirect costs, as well as the effect of delays in seeking care and test turnaround times. We used the Markov models to numerically estimate disability-adjusted life years (DALYs), pre-penalty costs, and likelihood of antibiotics overuse per patient for fifteen different strategies in two example settings in Thailand, one with a higher probability of bacterial infections (Northern Thailand, Scenario A) and one with a higher probability of viral infections (Bangkok, Scenario B). We found that empirical antibiotic treatment to all patients always incurs the lowest pre-penalty cost (Scenario A: $47.5/patient, $100.6/patient, $149.5/patient for patients seeking care on day one, day four, and day ten respectively; Scenario B: $94.1/patient, $108.7/patient, $122.1/patient on day one, day four, and day ten respectively), and the lowest DALYs, (Scenario A: 0.2 DALYs/patient, 0.9 DALYs/patient, 1.7 DALYs/patient on day one, day four, and day ten, respectively; Scenario B: 0.5 DALYs/patient, 0.7 DALYs/patient, 0.9 DALYs/patient on day one, day four, and day ten, respectively). However, such strategy resulted in the highest proportion of antibiotic overuse per patient (Scenario A: 38.1%, 19.3%, 7.5% on day one, day four, and day ten, respectively; Scenario B: 82.9%, 42.1%, 16.3% on day one, day four, and day ten, respectively). Consequently, empirical antibiotic treatment became suboptimal with antibiotic overuse penalties above $12,800/course, $18,400/course, $23,900/course for patients presenting on day one, day four, and day ten in Scenario A and above $1,100/course, $1,500/course, $1,600/course for patients presenting on day one, day four, and day ten in Scenario B.

CONCLUSIONS

Empirical antibiotic treatment to all patients provided the best outcomes if antibiotic overuse was not the primary concern or if presenting with viral disease (such as dengue) was unlikely. Empirical antibiotic treatment to severe patients only was in most cases not beneficial. Otherwise, strategies involving diagnostic tests became optimal. In particular, our results indicated that single test strategies (bacterial RDT or viral PCR) were optimal in regions with a greater probability of presenting with viral infection. PCR-led strategies (e.g., parallel bacterial PCR, or multiplex PCR) are robust under parameter uncertainty (e.g., with uncertain disease occurrence probabilities).

The Challenge of Transparency and Validation in Health Economic Decision Modelling: A View from Mount Hood

Transparency in health economic decision modelling is important for engendering confidence in the models and in the reliability of model-based cost-effectiveness analyses. The Mount Hood Diabetes Challenge Network has taken a lead in promoting transparency through validation with biennial conferences in which diabetes modelling groups meet to compare simulated outcomes of pre-specified scenarios often based on the results of pivotal clinical trials. Model registration is a potential method for promoting transparency, while also reducing the duplication of effort. An important network initiative is the ongoing construction of a diabetes model registry (https://www.mthooddiabeteschallenge.com). Following the 2012 International Society for Pharmacoeconomics and Outcomes Research and the Society of Medical Decision Making (ISPOR-SMDM) guidelines, we recommend that modelling groups provide technical and non-technical documentation sufficient to enable model reproduction, but not necessarily provide the model code. We also request that modelling groups upload documentation on the methods and outcomes of validation efforts, and run reference case simulations so that model outcomes can be compared. In this paper, we discuss conflicting definitions of transparency in health economic modelling, and describe the ongoing development of a registry of economic models for diabetes through the Mount Hood Diabetes Challenge Network, its objectives and potential further developments, and highlight the challenges in its construction and maintenance. The support of key stakeholders such as decision-making bodies and journals is key to ensuring the success of this and other registries. In the absence of public funding, the development of a network of modellers is of huge value in enhancing transparency, whether through registries or other means.

Are Nonpharmacologic Interventions for Chronic Low Back Pain More Cost Effective Than Usual Care? Proof of Concept Results From a Markov Model

STUDY DESIGN

Markov model.

OBJECTIVE

Examine the 1-year effectiveness and cost-effectiveness (societal and payer perspectives) of adding nonpharmacologic interventions for chronic low back pain (CLBP) to usual care using a decision analytic model-based approach.

SUMMARY OF BACKGROUND DATA

Treatment guidelines now recommend many safe and effective nonpharmacologic interventions for CLBP. However, little is known regarding their effectiveness in subpopulations (e.g., high-impact chronic pain patients), nor about their cost-effectiveness.

METHODS

The model included four health states: high-impact chronic pain (substantial activity limitations); no pain; and two others without activity limitations, but with higher (moderate-impact) or lower (low-impact) pain. We estimated intervention-specific transition probabilities for these health states using individual patient-level data from 10 large randomized trials covering 17 nonpharmacologic therapies. The model was run for nine 6-week cycles to approximate a 1-year time horizon. Quality-adjusted life-year weights were based on six-dimensional health state short form scores; healthcare costs were based on 2003 to 2015 Medical Expenditure Panel Survey data; and lost productivity costs used in the societal perspective were based on reported absenteeism. Results were generated for two target populations: (1) a typical baseline mix of patients with CLBP (25% low-impact, 35% moderate-impact, and 40% high-impact chronic pain) and (2) high-impact chronic pain patients.

RESULTS

From the societal perspective, all but two of the therapies were cost effective (<$50,000/quality-adjusted life-year) for a typical patient mix and most were cost saving. From the payer perspective fewer were cost saving, but the same number was cost-effective. Assuming all patients in the model have high-impact chronic pain increases the effectiveness and cost-effectiveness of most, but not all, therapies indicating that substantial benefits are possible in this subpopulation.

CONCLUSION

Modeling leverages the evidence produced from clinical trials to provide more information than is available in the published studies. We recommend modeling for all existing studies of nonpharmacologic interventions for CLBP.

LEVEL OF EVIDENCE

4.

Estimating Long-Term Drinking Patterns for People with Lifetime Alcohol Use Disorder

Background. There is a lack of data on alcohol consumption over time. This study characterizes the long-term drinking patterns of people with lifetime alcohol use disorders who have engaged in treatment or informal care. Methods. We developed multinomial logit models using the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) to estimate short-term transition probabilities (TPs) among the 4 World Health Organization drinking risk levels (low, medium, high, and very high risk) and abstinence by age, sex, and race/ethnicity. We applied an optimization algorithm to convert 3-year TPs from NESARC to 1-year TPs, then used simulated annealing to calibrate TPs to a propensity-scored matched set of participants derived from a separate 16-year study of alcohol consumption. We validated the resulting long-term TPs using NESARC-III, a cross-sectional study conducted on a different cohort. Results. Across 24 demographic groups, the 1-year probability of remaining in the same state averaged 0.93, 0.81, 0.49, 0.51, and 0.63 for abstinent, low, medium, high, and very high-risk states, respectively. After calibration to the 16-year study data (N = 420), resulting TPs produced state distributions that hit the calibration target. We find that the abstinent or low-risk states are very stable, and the annual probability of leaving the very high-risk state increases by about 20 percentage points beyond 8 years. Limitations. TPs for some demographic groups had small cell sizes. The data used to calibrate long-term TPs are based on a geographically narrow study. Conclusions. This study is the first to characterize long-term drinking patterns by combining short-term representative data with long-term data on drinking behaviors. Current research is using these patterns to estimate the long-term cost effectiveness of alcohol treatment.

Challenges and Opportunities Associated with Incorporating New Evidence of Drug-Mediated Cardioprotection in the Economic Modeling of Type 2 Diabetes: A Literature Review

INTRODUCTION

Cardiovascular disease is a leading cause of mortality in people with type 2 diabetes mellitus (T2DM). Beginning in 2015, long-term cardiovascular outcomes trials (CVOTs) have reported cardioprotective benefits for two classes of diabetes drugs. In addition to improving the lives of patients, these health benefits affect relative value (i.e., cost-effectiveness) of these agents compared with each other and especially compared with other agents. While long-term CVOT data on hard outcomes are a great asset, economic modeling of the value of this cardioprotection faces many new empirical challenges. The aim of this study was to identify different approaches used to incorporate drug-mediated cardioprotection into T2DM economic models, to identify pros and cons of these approaches, and to highlight additional considerations.

METHODS

A review of T2DM modeling applications (manuscript or conference abstracts) that included direct cardioprotective effects was conducted from January 2015 to September 2018. Model applications were classified on the basis of the mechanism used to model cardioprotection [i.e., directly via hazard ratios (HRs) for cardiovascular outcomes or indirectly via biomarker mediation]. Details were extracted and the studies were evaluated.

RESULTS

Five full-length articles and 16 conference abstracts (of which 11 posters were found) qualified for study inclusion. While the approaches used were diverse, the five full-length publications and all but two of the abstracts modeled cardioprotection used direct HRs from the relevant CVOT. The remaining two posters modeled cardioprotection using CVOT HRs in combination with treatment effects mediated through known risk factors.

CONCLUSION

The classification of empirical methods in cardioprotection was intended to facilitate a better understanding of the pros and cons of different methodologies. A substantial diversity was observed, though most used trial HRs directly. Given the differences observed, we believe that diabetes modelers and other stakeholders can benefit from a formal discussion and evolving consensus.

FUNDING

Janssen Global Services, LLC (Raritan, NJ, USA).

Use of Decision Modelling in Economic Evaluations of Diagnostic Tests: An Appraisal and Review of Health Technology Assessments in the UK

Diagnostic tests play an important role in the clinical decision-making process by providing information that enables patients to be identified and stratified to the most appropriate treatment and management strategies. Decision analytic modelling facilitates the synthesis of evidence from multiple sources to evaluate the cost effectiveness of diagnostic tests. This study critically reviews the methods used to model the cost effectiveness of diagnostic tests in UK National Institute for Health Research (NIHR) Health Technology Assessment (HTA) reports. UK NIHR HTA reports published between 2009 and 2018 were screened to identify those reporting an economic evaluation of a diagnostic test using decision analytic modelling. Existing decision modelling checklists were identified in the literature and a modified checklist tailored to diagnostic economic evaluations was developed, piloted and used to assess the diagnostic models in HTA reports. Of 728 HTA reports published during the study period, 55 met the inclusion criteria. The majority of models performed well with a clearly defined decision problem and analytical perspective (89% of HTAs met the criterion). The model structure usually reflected the care pathway and progression of the health condition. However, there are areas requiring improvement. These are predominantly systematic identification of treatment effects (20% met), poor selection of comparators (50% met) and assumed independence of tests used in sequence (32% took correlation between sequential tests into consideration). The complexity and constraints of performing decision analysis of diagnostic tests on costs and health outcomes makes it particularly challenging and, as a result, quality issues remain. This review provides a comprehensive assessment of modelling in HTA reports, highlights problems and gives recommendations for future diagnostic modelling practice.

Systematic review of utility values used in the pharmacoeconomic evaluations for schizophrenia: implications on cost-effectiveness results

Background and Objectives: Utility elicitation studies for schizophrenia generate different utility values for the same health states. We reviewed utility values used in schizophrenia pharmacoeconomic evaluations and evaluated the impact of their selection on the incremental cost-effectiveness ratio (ICER). Methods: A systematic search was performed in Medline and Embase. Health state definitions, associated utility values, elicitation studies, and value selection processes were extracted. Sets of utility values for all schizophrenia health states were used in a cost-effectiveness model to evaluate the ICER. Results: Thirty-five cost-utility analyses (CUAs) referring to 11 utility elicitation studies were included. The most frequent health states were 'stable' (28 CUAs, 7 utility elicitation studies, 10 values, value range 0.650-0.919), 'relapse requiring hospitalisation' (18, 5, 7, 0.270-0.604), 'relapse not requiring hospitalisation' (18, 5, 10, 0.460-0.762), and 'relapse only' (10, 5, 6, 0.498-0.700). Seventeen sets of utility values were identified with difference in utility values between relapse and stable ranging from -0.358 to -0.050, resulting in ICERs ranging from -56.2% to +222.6% from average. Conclusion: The use of utility values for schizophrenia health states differs among CUAs and impacts on the ICER. More rigorous and transparent use of utility values and sensitivity analysis with different sets of utility values are suggested for future CUAs.

Cost-effectiveness of physical activity interventions in adolescents: model development and illustration using two exemplar interventions

OBJECTIVE

To develop a model to assess the long-term costs and health outcomes of physical activity interventions targeting adolescents.

DESIGN

A Markov cohort simulation model was constructed with the intention of being capable of estimating long-term costs and health impacts of changes in activity levels during adolescence. The model parameters were informed by published literature and the analysis took a National Health Service perspective over a lifetime horizon. Univariate and probabilistic sensitivity analyses were undertaken.

SETTING

School and community.

PARTICIPANTS

A hypothetical cohort of adolescents aged 16 years at baseline.

INTERVENTIONS

Two exemplar school-based: a comparatively simple, after-school intervention and a more complex multicomponent intervention compared with usual care.

PRIMARY AND SECONDARY OUTCOME MEASURES

Incremental cost-effectiveness ratio as measured by cost per quality-adjusted life year gained.

RESULTS

The model gave plausible estimates of the long-term effect of changes in physical activity. The use of two exemplar interventions suggests that the model could potentially be used to evaluate a number of different physical activity interventions in adolescents. The key model driver was the degree to which intervention effects were maintained over time.

CONCLUSIONS

The model developed here has the potential to assess long-term value for money of physical activity interventions in adolescents. The two applications of the model indicate that complex interventions may not necessarily be the ones considered the most cost-effective when longer-term costs and consequences are taken into account.

A Latent Class Approach to Modeling Trajectories of Health Care Cost in Pediatric Cystic Fibrosis

Introduction. Estimating costs of medical care attributable to treatments over time is difficult due to costs that cannot be explained solely by observed risk factors. Unobserved risk factors cannot be accounted for using standard econometric techniques, potentially leading to imprecise prediction. The goal of this work is to describe methodology to account for latent variables in the prediction of longitudinal costs. Methods. Latent class growth mixture models (LCGMMs) predict class membership using observed risk factors and class-specific distributions of costs over time. Our motivating example models cost of care for children with cystic fibrosis from birth to age 17. We compare a generalized linear mixed model (GLMM) with LCGMMs. Both models use the same covariates and distribution to predict average costs by combinations of observed risk factors. We adopt a Bayesian estimation approach to both models and compare results using the deviance information criterion (DIC). Results. The 3-class LCGMM model has a lower DIC than the GLMM. The LCGMM latent classes include a low-cost group where costs increase slowly over time, a medium-cost group with initial higher costs than the low-cost group and with more rapidly increasing costs at older ages, and a high-cost group with a U-shaped trajectory. The risk profile-specific mixtures of classes are used to predict costs over time. The LCGMM model shows more delineation of costs by age by risk profile and with less uncertainty than the GLMM model. Conclusions. The LCGMM approach creates flexible prediction models when using longitudinal cost data. The Bayesian estimation approach to LCGMM presented fits well into cost-effectiveness modeling where the estimated trajectories and class membership can be used for prediction.

EWMA Document: Negative Pressure Wound Therapy

1. Introduction Since its introduction in clinical practice in the early 1990's negative pressure wounds therapy (NPWT) has become widely used in the management of complex wounds in both inpatient and outpatient care.¹ NPWT has been described as a effective treatment for wounds of many different aetiologies^2,3 and suggested as a gold standard for treatment of wounds such as open abdominal wounds,^4-6 dehisced sternal wounds following cardiac surgery^7,8 and as a valuable agent in complex non-healing wounds.^9,10 Increasingly, NPWT is being applied in the primary and home-care setting, where it is described as having the potential to improve the efficacy of wound management and help reduce the reliance on hospital-based care.¹¹ While the potential of NPWT is promising and the clinical use of the treatment is widespread, highlevel evidence of its effectiveness and economic benefits remain sparse.^12-14 The ongoing controversy regarding high-level evidence in wound care in general is well known. There is a consensus that clinical practice should be evidence-based, which can be difficult to achieve due to confusion about the value of the various approaches to wound management; however, we have to rely on the best available evidence. The need to review wound strategies and treatments in order to reduce the burden of care in an efficient way is urgent. If patients at risk of delayed wound healing are identified earlier and aggressive interventions are taken before the wound deteriorates and complications occur, both patient morbidity and health-care costs can be significantly reduced. There is further a fundamental confusion over the best way to evaluate the effectiveness of interventions in this complex patient population. This is illustrated by reviews of the value of various treatment strategies for non-healing wounds, which have highlighted methodological inconsistencies in primary research. This situation is confounded by differences in the advice given by regulatory and reimbursement bodies in various countries regarding both study design and the ways in which results are interpreted. In response to this confusion, the European Wound Management Association (EWMA) has been publishing a number of interdisciplinary documents^15-19 with the intention of highlighting: The nature and extent of the problem for wound management: from the clinical perspective as well as that of care givers and the patients Evidence-based practice as an integration of clinical expertise with the best available clinical evidence from systematic research The nature and extent of the problem for wound management: from the policy maker and healthcare system perspectives The controversy regarding the value of various approaches to wound management and care is illustrated by the case of NPWT, synonymous with topical negative pressure or vacuum therapy and cited as branded VAC (vacuum-assisted closure) therapy. This is a mode of therapy used to encourage wound healing. It is used as a primary treatment of chronic wounds, in complex acute wounds and as an adjunct for temporary closure and wound bed preparation preceding surgical procedures such as skin grafts and flap surgery. Aim An increasing number of papers on the effect of NPWT are being published. However, due to the low evidence level the treatment remains controversial from the policy maker and health-care system's points of view-particularly with regard to evidence-based medicine. In response EWMA has established an interdisciplinary working group to describe the present knowledge with regard to NPWT and provide overview of its implications for organisation of care, documentation, communication, patient safety, and health economic aspects. These goals will be achieved by the following: Present the rational and scientific support for each delivered statement Uncover controversies and issues related to the use of NPWT in wound management Implications of implementing NPWT as a treatment strategy in the health-care system Provide information and offer perspectives of NPWT from the viewpoints of health-care staff, policy makers, politicians, industry, patients and hospital administrators who are indirectly or directly involved in wound management.

Decision models of prediabetes populations: A systematic review

AIMS

With evidence supporting the use of preventive interventions for prediabetes populations and the use of novel biomarkers to stratify the risk of progression, there is a need to evaluate their cost-effectiveness across jurisdictions. Our aim is to summarize and assess the quality and validity of decision models and model-based economic evaluations of populations with prediabetes, to evaluate their potential use for the assessment of novel prevention strategies and to discuss the knowledge gaps, challenges and opportunities.

MATERIALS AND METHODS

We searched Medline, Embase, EconLit and NHS EED between 2000 and 2018 for studies reporting computer simulation models of the natural history of individuals with prediabetes and/or we used decision models to evaluate the impact of treatment strategies on these populations. Data were extracted following PRISMA guidelines and assessed using modelling checklists. Two reviewers independently assessed 50% of the titles and abstracts to determine whether a full text review was needed. Of these, 10% was assessed by each reviewer to cross-reference the decision to proceed to full review. Using a standardized form and double extraction, each of four reviewers extracted 50% of the identified studies.

RESULTS

A total of 29 published decision models that simulate prediabetes populations were identified. Studies showed large variations in the definition of prediabetes and model structure. The inclusion of complications in prediabetes (n = 8) and type 2 diabetes (n = 17) health states also varied. A minority of studies simulated annual changes in risk factors (glycaemia, HbA1c, blood pressure, BMI, lipids) as individuals progressed in the models (n = 7) and accounted for heterogeneity among individuals with prediabetes (n = 7).

CONCLUSIONS

Current prediabetes decision models have considerable limitations in terms of their quality and validity and do not allow evaluation of stratified strategies using novel biomarkers, highlighting a clear need for more comprehensive prediabetes decision models.

Economic evaluations of public health implementation-interventions: a systematic review and guideline for practice

OBJECTIVES

Implementation interventions applied in public health are about using proven strategies to influence the uptake of evidence-based prevention and health promotion initiatives. The decision to invest in implementation has an opportunity cost, which can be overlooked. The purpose of this study was to assess the extent to which economic evaluations have been applied to implementation interventions in public health.

STUDY DESIGN

We conducted a systematic review of empirical studies examining the costs and consequences, cost-effectiveness or cost-benefit of strategies directed towards enhancing the implementation of public health interventions and policies in developed countries.

METHODS

The following databases were searched for English language publications reporting both effect measures and costs, from 1990 to current: MEDLINE, Embase, PsycINFO, CINAHL, EconLit, EPPI-Centre database of health promotion research, Cost-Effectiveness Analysis Registry, NHS Economic Evaluation Database, Informit and Scopus.

RESULTS

The search strategy returned 3229 records after duplicate removal, from which we included 14 economic evaluations. All the included evaluations were conducted and published after 2000. Twelve of the 14 evaluations were based on controlled trials and two reported hypothetical modelled scenarios. The methodologic rigour and compliance with reporting guidelines for economic evaluations was highly varied and not related to the publication date.

CONCLUSIONS

Our findings offer the first insight into the application and methodologic rigour of economic evaluations of implementation strategies supporting public health policies and interventions. To usefully inform public health policy and investment decisions, there needs to be greater application of economic evaluation to understand the cost-effectiveness of alternative implementation efforts. This review highlights the great paucity and mixed quality of the evidence on this topic and offers guidance by way of a checklist to improve the quality and reporting of future evaluations.